A community-based nutrition education intervention taught
48 Bangladeshi families with breast-feeding infants how to
improve the mothers' diet. The energy adequacy of the women's
diets and of 30 comparable controls averaged 65% + 14% of the
FAD/WHO/ UNU requirement at baseline and declined to 55% + 7%
immediately after the education (Post1) and to 52% + 6% after
eight months of study (Post2). This decline was probably a
seasonal effect resulting from lower food availability at Post1
and Post2. The adjusted declines in adequacy of treatments and
controls did not differ at Post1 ( - 9.9% v. - 9.5%; p = .806)
when behavioural changes were expected.

Adjusted declines from baseline to Post2 were
significantly less for treatments than controls ( - 10.1% v. -
15.5%; p =.001), but results may have been influenced by flooding
that affected food distribution and production. Arm
circumferences (MUAC) of both groups remained along the fifth
percentile of the international reference. No significant
differences were found between the average weight for age (WAZ)
or MUAC of the breast-fed children in the two groups, although a
greater percentage of control children became severely
malnourished (p =.011). The evaluation raises concerns about the
effectiveness of nutrition education for improving the diets of
poor women if given in isolation of programmes that make
improvements affordable.

Limited maternal breast-milk outputs, combined with limited
feeding of complementary foods to infants of weaning age,
contribute to the poor growth of Bangladeshi children in the
first and second years of life. The children grow well within the
first few months after birth, but before age 4 to 6 months weight
gains falter relative to international standards [1-3]. One study
documents 90% of rural girls and boys to be below the fifth
percentile of the National Center for Health Statistics (NCHS)
reference standards by ages 8 and 15 months respectively [4].

The little information available on maternal nutrition status
and trends in Bangladesh highlights the poor condition of these
women. Bangladesh is one of three countries in the world where
women have a shorter life expectancy than men [5]. The overall
poor maternal nutrition status is worsened by seasonal food
scarcity and frequent pregnancies [6]. Widespread maternal
undernutrition in Bangladesh extends to unborn children, and the
vicious cycle of chronic nutritional deprivation entraps each
successive generation.

Over one-fourth of all infants are born with low birth weight
[7] to mothers who produce, on average, less breast-milk than
well-nourished women [8-10]. Supporting these observations, a
national survey found pregnant and lactating women consumed only
70% of their energy requirement and 65% of their estimated
protein requirement [11]. Recent trends suggest that nutrient
intakes and nutrition status have declined in recent years
[12,13]. Expansion of rice and wheat production has been at the
expense of other sources of food, such as pulses, fruit,
vegetables, and fish in the post-Green Revolution period,
resulting in a less varied and balanced diet [13].

Numerous cultural food practices compound the problem. Despite
the tremendous nutritional needs of the often pregnant and
lactating women, men and children eat first and the women eat the
remaining food, if any [14, 15]. Whether they receive
proportionately less food than others is not clear. There is
convincing evidence from Bangladesh and India for food
discrimination against girls under age four years [3,16-19];
however, the evidence is not strong for sex discrimination for
adults, when considering total food intake (energy) throughout
the day compared with requirements [16, 17, 20-24]. Studies do
not always take the additional needs for pregnancy and lactation
into consideration [24], however, or the quality of the diet
aside from energy intake [25 26].

A rural woman's day is consumed with cooking, collecting
firewood and water, cleaning and caring for children and elders.
Women have no control over the food budget - the men buy and sell
food in the market. Nearly 80% of women have never been to school
and cannot read, write, or understand numbers at a functional
level [7]. Adding to this powerlessness, the newlywed goes to
live with her husband's family, often a less supportive
environment than her own parents' home.

Exposure to education and information can empower a woman to
maximize the few resources around her for the health of her
family [27, 28]. An education intervention to improve the diets
of weaning-age children, conducted in the same setting as this
study, resulted in greater energy intakes and weight gains of
treatment children compared with controls [29]. This study,
however, questions the sources of nutrition education alone in
improving maternal diets under conditions of extreme poverty and
possible discrimination against women in intrahousehold food
distribution. Nutrition messages were designed for the Bangladesh
Rural Advancement Committee's (BRAC) Child Survival Programme to
improve lactating women's diets. Field observations suggested
that, in general, the mothers wished to eat more during
lactation. Yet, despite the project's promotion of low-cost
traditional foods and inclusion of other family members in the
teaching, the mothers reported that financial barriers limited
their ability to comply with messages. This study evaluates the
impact of the messages on the dietary adequacy and nutrition
status of the women, and the growth of their breast-fed infants.
A discussion of the food costs imposed by these nutrition
messages is available elsewhere [30, 31].

From February to November 1987, BRAC and Tufts University
conducted a lactation intervention in a rural site in the
Harirampur subdistrict in the Manikganj district of Bangladesh.
This low-lying area on the banks of the Padma (Ganges) River was
selected because of its high rates of malnutrition and isolation
from other development projects [32]. The intent of the
intervention was to develop feasible messages through
community-based behavioural trials, that would ameliorate the
lactating mother's diet to improve her milk supply, her health,
and the growth of the breast-fed infant. The procedures followed
were in accordance with the guidelines of the Tufts University
Human Subjects Committee.

The field trial model is described in detail elsewhere [31,
33]. Briefly, eight village workers (VWs) were hired from the
local community. Additional staff were a supervisor,
anthropologist, and nutritionist. The preliminary messages, which
were developed by the VWs and technical staff in response to a
community needs assessment, encouraged the lactating mother to
eat an extra serving of all foods she normally ate at each meal,
consume adequate fluids, wash hands and utensils before eating,
and offer both breasts to the baby when breast-feeding.

The messages were then disseminated by volunteer mothers to
other lactating mothers tested, and revised on the basis of
observations and outcomes during the intervention. The home-based
approach to teaching was participatory and family oriented,
involving the mother, her husband, and her mother-in-law.
Following cultural norms, male VWs met with and taught the male
household members.

Sample

Using a BRAC census conducted in January 1987, we identified
treatment mothers in five villages with breast-fed infants living
near other families with young infants to whom they could
disseminate the educational messages. Control mothers with
breast-fed infants were recruited from five villages located
approximately one hour by foot away from the nearest intervention
village, using a BRAC baseline nutrition status survey conducted
in January as a sampling frame. A total of 78 lactating mothers
and their breast-fed infants (48 treatment, 30 control) were
followed for approximately eight months. The infants" ages
ranged from 0 to 11 months at baseline (over 80% were under 6
months) to 8 to 18 months at the final measure.

Missing data were primarily due to the child or mother being
absent on follow-up visits (e.g., visiting maternal relatives) or
the family's out-migration from the study area. In addition, one
treatment child died from an acute illness early in the study.

Data-collection and survey instruments

Baseline anthropometric, dietary, and socio-economic data were
collected on all sample households, and anthropometric, dietary,
and child morbidity data were collected monthly except during
serious flooding in August and September. Workers were trained in
anthropometry using methods developed by Zerfas [34]. Child
weight was measured with a portable 25 kg dial scale, and mother
and child arm-circumference measurements were taken with the TALC
tape [35]. The mother's and child's monthly 24-hour food recall
was recorded on a pre-tested instrument containing common
Bangladeshi foods [36, 37]. Child morbidity data consisted of
mother's monthly recall of the type of illness and approximate
number of days the child was sick.

Data analysis variable construction

The impact of the intervention was evaluated on the basis of
changes in pre- and post-education indicators for dietary
adequacy and nutrition status, after adjusting for baseline
(pre-education) differences between treatment and control groups.
The baseline measure was obtained during the rolling recruitment
in February-March. Two post-education indicators were used, Post1
in May-June, and Post2 in October-November. Evaluating at Post1,
when the average age of the children was only seven months,
allowed assessment of any changes in the mothers' diet on the
growth outcomes of the younger children who were predominantly
breast- fed, measured against the World Health Organization (WHO)
definitions [38]. This measurement was also before the severe
August floods, which may have altered the potential impact of the
nutrition education. Post2 allowed assessment of impact after a
longer follow-up.

Anthropometry

The changes in women's and children's mid-upper arm
circumference (MUAC) measurements were evaluated from the
baseline to the Post2 end point, but not at Post1 owing to a
large number of missing measurements. Age and sex of children
were controlled for in the child MUAC analyses.

Children's weights (available only on infants under six months
at recruitment) converted to Z scores (WAZ) according to the NCHS
and WHO standards for age and sex [39], were used for statistical
comparisons. Actual weights and percentage of median
weight-for-age (WAPM), using the same standards, were displayed
for descriptive purposes.

The baseline anthropometric variables were the first
measurements available during the February-March recruitment. For
controls, the first anthropometric measurements were obtained
during the last few days in January; however, for simplicity, the
baseline is referred to as beginning in February. Post1 and Post2
variables were the last measures available during May-June and
October-November respectively.

Dietary adequacy

The women's intakes of energy, protein, fat, vitamin A, and
iron were computed from the monthly 24hour recalls using
Bangladesh food composition tables [40] and US Department of
Agriculture tables [41], and expressed as a percentage of the
international recommendations [42, 43]. Because all mothers were
lactating throughout the study, and test weighings for
breast-milk output were not feasible, milk production and
(child's consumption) was estimated for each age in months from
research on a comparable Bangladeshi sample [8, 9].

In estimating the daily energy requirement, a conservative
estimate of the women's basal metabolic needs (BMR) was first
made on the basis of FAO/ WHO/UNU guidelines [42], using a
reference 40.4 kg woman [6]. The BMR was multiplied by a factor
of 1.7 for energy expenditure, derived by estimating energy
requirements for the daily activities of the rural Bangladeshi
woman [42]. An additional 500 kcal (2,094 kJ) was added for
adequate lactation [42, 44, 45] for a total daily requirement of
2,405 kcal (10,070 kJ).

The safe daily protein requirement for the non-lactating woman
was estimated to be 30.3 g, with an additional factor for
lactation varying from 16 to 11 g based on the age of her child
[42]. The protein content of non-animal foods was adjusted
assuming 85% digestibility and 75% amino acid score [42]. The
daily iron requirement was estimated at 15 mg [43]. The vitamin A
requirement was 3,900 IU (1,300 µg RE) if the mother's child was
under six months and 3,600 IU (1,200 µg RE) if the child was
over six months [43, 46].

Energy intakes from complementary foods were also computed for
the infants from 24-hour recalls, and expressed as a percentage
of ideal requirements (with and without breast-milk estimates),
using the NCHS median weight for the child's age and sex [39].
Energy requirements per kilogram of body weight for infants 0 to
12 months were derived from the FAO/WHO/UNU equation:
kcal/kg/day=[(123 - 8.9 (age)) + U.59 (age2) x 1.05.
For children 12 to 24 months, the estimated daily requirement was
105 kcal/kg (440/kJ/kg) [42].

The baseline dietary variables were taken as the first 24-hour
recall available. The Post1 and Post2 variables were created by
averaging all monthly 24hour recalls available during May-July
and October-November respectively.

Child morbidity

For analysis, the mother's monthly recall of the type and
duration of her breast-fed child's illness was categorized into
gastrointestinal illness (diarrhoea, dysentery, vomiting),
respiratory and oral infections (cold, cough, throat or mouth
infections), fever, measles, and other (skin or eye infections,
other minor illness). Combining all the available observations
for each child, the mean percentage of days per month the child
was sick with the illness in a respective category was computed
and used to control for the effects of morbidity on child growth.
Despite acknowledged limitations of the monthly recall for
morbidity reporting, the data can be expected to distinguish very
sick children from the generally healthy when it is used as a
control variable.

TABLE 1. Characteristics of sample mothers and their families

Characteristic

Treatment (n = 48)

Control
(n = 30)

Significance

Mother's age (yrs) (mean +
SD)

26 ± 6

28 ± 6

NSa

No. of household members
(mean + SD)

7 ± 3

6 ± 2

NSa

No. of mother's children
(mean + SD)

3 ± 2

3 ± 2

NSa

Mother's education (%)

NSa

none

71

77

some primary

4

0

completed primary

17

13

some secondary

8

10

Religion (%)

***b

Moslem

85

47

Hindu

15

53

Owns house and lot (%)

98

60

***b

Landless ( % )

42

93

***b

Tube well water source (%)

98

97

NSb

Bamboo, non-pit latrine (%)

90

90

NSb

Major source of income (%)

NSb

farmer

33

0

agricultural/skilled labour
19

20

government service

17

30

business

15

20

other

16

30

Calculated by t test.

Calculated by chi-square tests.

*p < .05; ***p <.001.

Socio-economic indicators

Socio-economic indicators collected at baseline were education
and literacy of household members, occupation, housing type,
amount of land, solvency, source of drinking water, latrine type,
and possessions. Scales for monetized household possessions or
traditional wealth, agricultural wealth, and
modernization/education were created for each household.
Acceptable internal consistencies of the scales were confirmed
using SPSSX's reliability program with Cronback's a [47].
Characteristics of sample mothers and families are presented in
table 1.

Statistical methods

The impact of the education intervention was determined by
examining the differences in the baseline, Post1, and Post2
measurements using analysis of covariance. Adjusted mean values
were calculated for treatment and controls for anthropometric and
dietary variables, controlling for wealth, mother's education,
morbidity, child age and sex, mother's age and baseline nutrition
status or nutrient intake. The McNemar non-parametric test for
changes from pre- to post-intervention was used to determine the
significance of changes in the number of severely undernourished
children in each treatment group. SPSSX was used for statistical
analysis. Statistical significance was defined as p < .05.

Table 2 summarizes the adjusted energy adequacies of the
mother's diets relative to estimated requirements. At baseline,
mothers in the control group were consuming significantly more
energy than those in the treatment group (p <.001). The
majority of controls were recruited during the beginning of
February, which was shortly after the major rice harvest. Owing
to the continuing enrolment in the education programme, the
majority of treatment mothers entered the study in March, which
was generally a less plentiful month, with greater food scarcity,
higher food prices, and lack of available work [15, 31]. For both
groups, however, the energy adequacy of the women's diets was
very poor, at only 65% + 14% (mean + SD) of their estimated
needs.

The adequacy of the mothers' energy intakes declined for both
groups over the first three months of the education programme
(Post1 55% + 7%). Although the decline was greater for the
controls, the difference was not statistically significant (p=
.806), even after controlling for other significant factors. The
mothers' dietary energy adequacy declined further from Post1 to
Post2 measure (52% + 6%). The (adjusted) decline over the total
eight months of the study was significantly greater (p= .001) for
the controls than for the treatment mothers (15.5% v. 1 0.1 % ).
The estimated decline in the mother's breast-milk production
(based on age of child) was not significant in predicting the
decline in her energy intake over time.

Means adjusted by analysis of covariance for significant
covariants and potential confounding variables (as listed
above). Baseline measurements taken in February-March, Post1
in May-July. and Post2 in October-November. B-Post1 and
B-Post2 compute the difference from baseline to Post1 and
Post2 respectively The average column averages all months
available.

*p < .05; **p < .01; ***p < .001;- not entered.

General characteristics of diets

The percentage of diet energy contributed by each food and
nutrient group was similar for both treatment and control
mothers. Figure 1 (see FIG. 1. Percentage of
diet energy from various food groups in diets of lactating
mothers by season, treatments, and controls combined)
combines both groups to illustrate the very high percentage
contributed by grain, which included rice and wheat (>80%).
The proportion from grain was lowest during February-March, when
the diet included more vegetables. Fruits, fish, other animal
foods, and lentils were consumed in very small quantities. Fats
from all food sources (oils, animal food, etc.) contributed only
5% of the total energy in the womens' high-bulk diets.

Protein and iron intakes paralleled trends in energy intake;
thus additional statistical comparisons between treatments and
controls for these nutrients were of no further value. In
general, protein adequacy was slightly better than energy
adequacy, even after adjusting for the low protein quality (60% +
8% v. 56% + 6% overall). Dietary iron intake was adequate,
averaging 116% + 20% over all the seasons, assuming a requirement
level of 15 ma/ day [43]. In addition to food sources analysed in
this study, the drinking water, often obtained from iron tube
wells, may have provided additional iron, although the absorption
may be low.

Vitamin A intakes were very low, averaging only 30% + 16% of
requirements throughout the study. Vitamin A consumption was
highest during Post1, when carotene-rich foods such as mangoes
were in season, and many dark green leafy vegetables were
plentiful and inexpensive. The increase in vitamin A intake from
the baseline to Post1 was significantly greater for the treatment
mothers than for the controls ( p = .023); however, by Post2 the
change in consumption was not significantly different between the
two groups (p= .333).

Changes in nutritional status

Mothers' arm circumference

Mothers' adjusted MUAC data are shown in table 3. The average
MUAC of the mothers in the treatment and control groups was
similar before education, with the average measurement
approximating the fifth percentile of the reference standard
[48]. Over the eight months of study, MUAC remained relatively
stable, with no significant group differences, controlling for
other significant factors.

There were no significant differences in nutrition status at
baseline, measured by either MUAC or WAZ, between the children
whose mothers received nutrition education and those who did not.
The nutrition status of both groups deteriorated over the study
period, as indicated by a decline in WAZ, but the changes were
not significantly different between the treatment and control
children for either WAZ or MUAC (tables 4 and 5). Table 6
provides descriptive data on the adequacy of complementary food
intake with and without breast-milk estimates for the sample of
children with weights at all three measures. No significant
differences in complementary food energy intake were found
between control and treatment children. Details of the
traditional complementary food composition and adequacy for a
similar sample are described elsewhere [29, 31].

TABLE 4. Adjusted mean mid-upper arm circumference (MUAC) of
breast-fed children before and after nutrition education

No significant treatment group differences were apparent in
child anthropometry, but the energy adequacy of the mother's diet
was significantly related to her child's WAZ and MUAC. Sex of the
child was a more significant prediction of child WAZ at baseline
(i.e., in the 3-month child) than at Post2 (average age 12
months), with boys faring slightly better than girls. Girls,
however, showed less decline in WAZ over the study period than
males. At Post2, no significant sex differences in WAZ were
apparent.

For MUAC, which includes a larger sample of children, there
were no significant sex differences at baseline after controlling
for other significant factors. By Post2, however, sex differences
were apparent, with boys having larger MUACs. This is expected,
since the measures are not standardized against a norm for age
and sex. At each point, the average MUAC for the treatment group
was slightly (although not significantly) higher than the
controls simply as an artefact of the slightly older age in this
sample (also not significant).